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<TITLE>CS674 Spring 1996 Course Materials</TITLE>
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<H1>
CS674 Spring 1996<br>
Introduction to Natural Language Understanding<br>
Course Materials
</H1>

<HR>

<UL>
<LI><!WA0><!WA0><!WA0><!WA0><A HREF="#1">Handouts</A>
<LI><!WA1><!WA1><!WA1><!WA1><A HREF="#2">Lecture Slides</A>
<LI><!WA2><!WA2><!WA2><!WA2><A HREF="#3">Homeworks</A>
<LI><!WA3><!WA3><!WA3><!WA3><A HREF="#4">Project Information</A>
</UL>

<HR>

<H2><A NAME = "1">Handouts</a></H2>

<!WA4><!WA4><!WA4><!WA4><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/handouts/syllabus.ps">
(Tentative) Course Syllabus </a><br>
<!WA5><!WA5><!WA5><!WA5><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/handouts/course-policies.ps">
Course Description and Policies </a><br>

<HR>

<H2><A NAME = "2">Lecture Slides</a></H2>

<p>
<H3><em>Introduction to Natural Language Understanding</em></H3>

(Jan 22) <!WA6><!WA6><!WA6><!WA6><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/lectures/lecture01.ps"> Introduction to the Field of NLP </a><em>(Ch 1)</em><br>

(Jan 24) <!WA7><!WA7><!WA7><!WA7><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/lectures/lecture02.ps"> Stages of Processing</a><br>

<p>
<H3><em>Syntactic Analysis</em></H3>


(Jan 29) <!WA8><!WA8><!WA8><!WA8><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/lectures/lecture03.ps">
	 Grammars and Sentence Structure, Top-down and Bottom-up Parsing </a><em>(Ch 3.1-3.3)</em><br>
(Jan 31) <!WA9><!WA9><!WA9><!WA9><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/lectures/lecture04.ps"> 
	 Chart Parsing </a><em>(Ch 3.4)</em><br>
(Feb 5)  <!WA10><!WA10><!WA10><!WA10><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/lectures/lecture05.ps"> 
	 Feature Systems and Augmented Grammars </a> <em>(Ch 4.1-4.5)</em><br>  
(Feb 7) <!WA11><!WA11><!WA11><!WA11><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/lectures/lecture06.ps"> 
        Human Preferences in Parsing, Partial Parsing </a> <em>(Ch 6.1, 6.5)</em><br>

<p>
<H3><em>Semantic Analysis</em></H3>

(Feb 12) <!WA12><!WA12><!WA12><!WA12><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/lectures/lecture07.ps"> 
	Word Senses and Ambiguity,Representing Verbs and States </a> 
	<em>(Ch 8.1-8.6)</em><br>  
(Feb 14) <!WA13><!WA13><!WA13><!WA13><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/lectures/lecture08.ps"> 
	Thematic Roles, Semantic Interpretation </a> <em>(Ch 9.1-9.4)</em><br>
(Feb 19) <!WA14><!WA14><!WA14><!WA14><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/lectures/lecture09.ps"> 
	Selectional Restrictions, Handling Intrasentential Word Sense Ambiguity </a><em>
	(Ch 10.1--10.2)</em> <br>

<p>
<H3><em>Conceptual Sentence Analysis</em></H3>
(Feb 21) <!WA15><!WA15><!WA15><!WA15><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/lectures/lecture10.ps"> 
	The CIRCUS Parser, Preference Semantics, Data-Driven Semantics </a><br>

<p>
<H3><em>Context and World Knowledge</em></H3>

(Feb 26)<!WA16><!WA16><!WA16><!WA16><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/lectures/lecture11.ps"> 
   	The Problem of Inference, Expectation-Based Text Analysis </a><em>(Ch 15.1-15.7)</em><br>
(Feb 28) <!WA17><!WA17><!WA17><!WA17><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/lectures/lecture12.ps"> 
	Using Knowledge About Action and Causality, Scripts </a><br>
(Mar 4) <!WA18><!WA18><!WA18><!WA18><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/lectures/lecture13.ps"> 
 	Plan-Based Understanding of Text </a> <br>
(Mar 6) Discourse Context, History Lists, Centering <em>(Ch 14.1-14.3)</em>
	<em>***Guest lecture*** <br>(Scott Mardis)</em><br>

<p>
<H3><em>Current Trends: Evaluation, Learning, Statistics</em></H3>

(Mar 11) <!WA19><!WA19><!WA19><!WA19><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/lectures/lecture15.ps"> 
        Evaluating NLU Systems </a> <br>
(Mar 13) <!WA20><!WA20><!WA20><!WA20><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/lectures/lecture16.ps"> 
        HMM's <em>(Ch 7.1-7.4)</em> </a> <br>
<em> ***** Spring Break ***** </em><br>
(Mar 25) <!WA21><!WA21><!WA21><!WA21><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/lectures/lecture17.ps">
        Part-of-Speech Tagging </a> <br>
(Mar 27) <!WA22><!WA22><!WA22><!WA22><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/lectures/lecture18.ps">
        Probabilistic Context-Free Grammars, Best-First Parsing </a>
        <em>(Ch 7.5-7.7)</em><br>
(Apr 1) <!WA23><!WA23><!WA23><!WA23><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/lectures/lecture19.ps">
        Context-Dependent Best-First Parsing, Statistical Word Sense
        Disambiguation </a> <em>(Ch 10.4-10.6)</em><br>  
(Apr 3) <!WA24><!WA24><!WA24><!WA24><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/lectures/lecture20.ps">
        A Localist Connectionist Approach to Sentence Analysis</a><br>
(Apr 8) <!WA25><!WA25><!WA25><!WA25><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/lectures/lecture21.ps">
	Transformation-Based Error-Driven Learning and NLP</a><br>
(Apr 10) Corpus- and MRD-based Methods for Word-Sense Disambiguation<br>
	<em>***Guest lecture*** (Julia Komissarchik)</em><br>
(Apr 15) Information Extraction as a Basis for High-Precision Text Categorization<br>
	<em>No on-line slides for this lecture.</em><br>
(Apr 17) A Case-Based Approach to Ambiguity Resolution<br>
(Apr 22) NO CLASS<br>
(Apr 24) Project Presentations<br>
(Apr 29) Project Presentations<br>
(May 1) Project Presentations<br>

<HR>
<H2><A NAME = "3">Homework Assignments</a></H2>
<ul>
<li><!WA26><!WA26><!WA26><!WA26><a href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/hwk/hwk1.ps">Homework 1</a> (due Wednesday, Feb 7)
<li><!WA27><!WA27><!WA27><!WA27><a href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/hwk/hwk2.ps">Homework 2</a> (due Friday, Feb 23)
<li><!WA28><!WA28><!WA28><!WA28><a href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/hwk/hwk3.ps">Homework 3</a> (due Friday, Mar 15)
	<ul>
	<li><!WA29><!WA29><!WA29><!WA29><a href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/hwk/tr-ex.html">Example of Thematic Roles</a> 
	</ul>
<li><!WA30><!WA30><!WA30><!WA30><a href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/hwk/hwk4.ps">Homework 4</a> (<em>optional</em>) 
(due Wednesday, Mar 27) 
</ul>

<HR>
<H2><A NAME = "4">Project Information</a></H2>

<a name = "4.1">
<h3>What to Turn in for the Proposal</h3>
<ul>
<li>Project proposals are <b>due on Monday, March 11</b>, 
but I'd be happy to look at them before then.

<li>The project proposal should contain a short description of:

<ol>
<li> the topic/problem in which you're interested
<li> the papers that you'll read (if you're doing a "reading" project)
<li> a description of the general approach you plan to use to solve the problem
 (if you're doing a "programming" project)
<li> plan for evaluation of the theory/technique (for both types of project)
</ol>
</ul>

<hr>

<a name = "4.2">
<h3>What to Turn in for the Project</h3>

Official due date: Friday 5/3.  We'll accept projects without penalty
until 5:00, Friday 5/10.

<h4>Programming projects:</h4>

<b>Final Writeup for Programming Projects (just a few pages):</b>
<ol>
   <li> Problem description
   <li> Description of general approach
   <li> Description and results of evaluation
   <li> Discussion. (what worked; what didn't work; options you'd
	like to have tried; analysis of the results; etc.)
   <li> I'd also like to see any code that you wrote and a few short
	traces of the system in action (if that makes sense for your project).
</ol>

<p>

<b>In-Class Presentation:</b> ~7 minutes in length. Should include
an overview of the problem; your solution; evaluation method and
results. 

<p>

<h4>Non-Programming projects:</h4>

<b>Final Writeup for Non-programming Projects.</b> This will vary for
each person, but in general, the final writeup for non-programming
projects will probably contain a description of the problem that you
looked at; a summary of the papers that you read; a critique of the
existing approaches; your attempt at an evaluation of the the
theory/algorithms presented in the papers on real text.

<p>

<b>In-Class Presentation:</b> For non-programming projects, the
in-class presentation should be a synopsis of what you'll include in
the paper.  You'll have to leave a lot out of course...

<p>

<hr>

<h4>Programming Projects from Last Year's Class</h4>
<ul>
<li><b>Grammar Induction using Genetic Algorithms</b><br>
This project implements a grammar generator using genetic algorithms.

<li><b>AutoSlog and FALCON:  Automated Lexicon Construction</b><br>
This paper evaluates the performance of AutoSlog and FALCON as lexicon
constructors.

<li><b>A Preposition Attacher</b><br>
This project uses a matching algorithm for preposition attachment.

<li><b>Statistical Word Sense Disambiguation</b><br>
This project implements a number of related statistical methods for word-sense
disambiguation and evaluates the method using examples from the Brown corpus.

<li><b>Automated English-Esperanto Translation</b><br>
This project implements a limited English-Esperanto translator by extending
James Allen's bottom-up parser.

<li><b>An Implementation of a Method for Word Sense Disambiguation</b><br>
This project implements a relaxation network approach (like CIRCUS's) for word-sense
disambiguation. It is based on: <cite>Large Neural Networks
for the Resolution of Lexical Ambiguity</cite> by J. Veronis and N. Ide.

<li><b>The Viterbi Algorithm and Smoothing</b><br>
This project is an implementation of a part-of-speech tagger using a Hidden
Markov Model, a smoothed bigram language model, and the Viterbi algorithm.
</ul>

<h4>Reading Projects from Last Year's Class</h4>
<ul>
<li><b>Topics in Intelligent Multimedia/Multimodal Interface</b><br>
This paper examines two existing systems that incorporate intelligent
multimedia/multinodal interfaces (WIP and COMET).
<li><b>Using FOIL for WH-Phrase Disambiguation</b><br>
This paper examines ways to use FOIL for  WH-phrase disambiguation.  (FOIL is a
supervised learning algorithm for acquiring concepts in first-order logic.)
<li><b>Natural Language Understanding of the Japanese Language</b><br>
This paper summarizes issues for understanding Japanese.
<li><b>Approaches to Automated Question Answering</b><br>
This paper addresses issues in understanding and replying to questions given
in English.
<li><b>Word Boundary Detection in Continuous Speech Recognition: Application of
Phonological Constraints</b><br> 
This paper looks at three models that use broad class, phonemic sequence, and 
allophonic constraints to facilitate word boundary detection.
<li><b>Computer Understanding of Conventional Metaphoric Language</b><br>
This paper looks at MIDAS (Metaphor Interpretation, Denotation and Acquisition System)
for understanding conventional metaphor. 
<li><b>An Analysis of Transformation-Based Part of Speech Tagging</b><br>
This paper critiques the an article on transformation-based
part of speech tagging.
<li><b>Neural Networks and NLU</b><br>
This paper looks at neural network applications for natural language understanding.
<li><b>Pronominal Anaphora Resolution</b><br>
This paper describes four approaches to the computational task of resolving
the pronoun referents.
<li><b>Harmonic Grammars and Unaccusativity</b><br>
This paper looks at Harmonic Grammars developed by Smolensky, Legendre and
Miyata.
</ul>

<hr>


<!WA31><!WA31><!WA31><!WA31><A href="http://www.cs.cornell.edu/Info/Courses/Spring-96/CS674/CS674.html">Return to CS674 home page</a>

